HCV genetic diversity can be used to infer infection recency and time since infection. Viruses
HIV-1 genetic diversity can be used to infer time since infection and infection recency. Carlisle et al. aimed to investigate whether the same next-generation sequencing (NGS-) derived-diversity method can be applied to HCV, and to identify the region of the genome over which it is most informative to measure diversity.
The authors included 72 HCV/HIV-1 coinfected participants of the Swiss HIV Cohort Study, for whom reliable estimates of infection date and viral sequences were available. Average pairwise diversity (APD) was calculated over each codon position for the entire open reading frame of HCV. Utilizing cross validation, they evaluated the correlation of APD with time since infection and its ability to infer time since infection via a linear model. They additionally studied the ability of diversity to classify infections as recent (infected for <1 year) or chronic, using receiver-operator-characteristic area under the curve (ROC-AUC) in 50 patients whose infection could be unambiguously classified as either recent or chronic.
Measuring HCV diversity over third or all codon positions gave similar performances, and notable improvement over first or second codon positions. APD calculated over the entire genome enabled classification of infection recency (ROC-AUC = 0.76). Additionally, APD correlated with time since infection (R2 = 0.33) and could predict time since infection (mean absolute error = 1.67 years). Restricting the region over which APD was calculated to E2-NS2 further improved accuracy (ROC-AUC = 0.85, R2 = 0.54, mean absolute error = 1.38 years).
In conclusion, the study found a substantial correlation between time since infection and average pairwise diversity. Based on this, the authors could show that infection recency and time since infection can be accurately predicted by using average pairwise diversity. Thus, in the cases where samples from HCV-infected persons are sequenced, this method provides recency and date of infection information as free by-products of standard NGS sequencing, which can add to such monitoring studies.